Senior AI/ML Engineer, Knowledge & Retrieval Systems

Summary

Join Onebrief, a revolutionary platform for military staff workflows, as a Machine Learning Engineer. You will transform complex military operational plans into actionable knowledge, designing and implementing scalable systems for data retrieval. Lead the design of hybrid retrieval pipelines using semantic search, keyword methods, and graph reasoning. Optimize embeddings for specialized content and build resilient systems for rapid decision-making. Collaborate with ML, product, and domain experts. This role requires hands-on experience building real-world retrieval and knowledge-driven systems. Onebrief offers a fast-paced startup environment and the opportunity to work with cutting-edge technologies.

Requirements

• B.S. in Computer Science, Engineering, or equivalent practical experience
• 2–4 years of experience in applied ML, information retrieval, or knowledge systems
• Strong Python programming skills
• Experience with semantic search, vector stores, and retrieval system design
• Comfort with ETL workflows and structured, domain-specific datasets
• Understanding of distributed systems and performance trade-offs
• Familiarity with testing and evaluating information retrieval systems
• Understanding of security considerations in data handling and system design

Responsibilities

• Design and build hybrid retrieval systems that combine semantic, symbolic, and graph-based methods
• Develop pipelines to encode and retrieve operational knowledge using LLMs, vector databases, and custom chunking/indexing strategies
• Build and optimize retrieval-augmented generation (RAG) systems for high-stakes environments
• Architect knowledge graphs and integrate them into retrieval workflows
• Collaborate with ML, product, and domain experts to transform requirements into deployable solutions

Preferred Qualifications

• Experience designing chunking/indexing pipelines for large, domain-specific datasets
• Experience designing or deploying knowledge graphs in real-world systems
• Experience with offline-capable and edge-deployable ML systems
• Familiarity with containerization and orchestration tools (Docker, Kubernetes)
• Exposure to geospatial data and reasoning systems
• Background in defense, national security, or other mission-critical domains
• Understanding of LLM prompt engineering, context window optimization, and RAG techniques
• Advanced degree (M.S. or PhD) in a relevant field is a plus